Univariate data manipulation and plots
Nick Toimieri
sys.date()
1 Triggers and Settings
2 Import fish and manipulate data a bit
Minimum vis for fish analysis = 2-m
Kelp depths = 5 -m Fish depths = 5, 10 -m Inv depths = 5 -m
Visibility data for 2015 are fake. DI was bad and set at 1.0 m; other sites set at 3.0 m
3 FISH
3.1 Rockfish YOY
## `summarise()` has grouped output by 'site', 'year'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year'. You can override using the `.groups` argument.## Joining, by = "taxa"
3.2 Fish
Fish depth = 5, 10
## Joining, by = "taxa"
## Fish and YOY plot
Note: I have yellowtail here, but they are not in the multivariate stuff since we reall only saw them once.
3.3 Fish and YOY facet by site x year
## Joining, by = "taxa"
## Joining, by = "taxa"
4 ALGAE
Kelp depth = 5
## `summarise()` has grouped output by 'year', 'site', 'transect', 'species', 'zone', 'area'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year', 'site', 'species', 'zone', 'area'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year', 'site', 'species', 'zone'. You can override using the `.groups` argument.## Joining, by = "site"4.1 Nereocystis at Tatoosh
4.2 Nero and Macro
## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year', 'site'. You can override using the `.groups` argument.
4.3 Big three: Nero, Macro, Ptero
Plot the big 3 species: Macro, Nero, Ptero
4.3.1 Big three 5 m only
4.3.2 Big three - Coastwide
## `summarise()` has grouped output by 'site', 'year'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year'. You can override using the `.groups` argument.
4.3.3 Coastwide 5m only
## `summarise()` has grouped output by 'site', 'year'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year'. You can override using the `.groups` argument.
5 INVERTEBRATES
## `summarise()` has grouped output by 'year', 'site', 'transect', 'observer', 'species', 'zone', 'area', 'taxa'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year', 'site', 'species', 'zone', 'area'. You can override using the `.groups` argument.5.1 Summed Urchins
## `summarise()` has grouped output by 'year', 'site', 'transect', 'observer', 'zone', 'area'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year', 'site', 'zone', 'area'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year', 'site', 'transect', 'observer', 'area', 'zone'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override using the `.groups` argument.
Max total urchin density at Tatoosh
5-m = 4.0503465 m^-2 10-m = 10.0752194 m^-2
5.2 Urchins by species
Probably worth dropping into the supplement to show that it was mostly purple urchins. Partly interesting because there is no purple urchin fishery, but there is a red one. I think.
## `summarise()` has grouped output by 'year', 'site', 'transect', 'observer', 'zone', 'area'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override using the `.groups` argument.
Max total urchin density at Tatoosh
5-m = 3.7336798 m^-2 10-m = 9.5052194 m^-2
## `summarise()` has grouped output by 'site', 'year'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year'. You can override using the `.groups` argument.
Purple urchin density in 2015 = 0.0116667 urchins per m^2 Purple urchin density in 2015 = 1.7637508 urchins per m^2
Increase was 151.1786432 fold.
Purple urchin density in 2015 = 0.7299487 urchins per m^2
Density compared to 2015 was 62.5670286 fold.
5.3 Seastars
## `summarise()` has grouped output by 'year', 'site', 'transect', 'observer', 'area', 'zone'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year'. You can override using the `.groups` argument.
Ugly..no aliby..
## `summarise()` has grouped output by 'year', 'site', 'transect', 'observer', 'zone', 'area'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override using the `.groups` argument.
6 Output data for multivariate statistics
6.1 Combine kelp, fish, and inverts for capscale analysis
Not yet transformed to wide format in order to retain SD & SE info upon saving out. Transform in the Multiariate analysis rmd.
Output data files to use for multivariate ordinations.
Use these files and not raw files. Kelp and invert data have been converted to density to account for different transect lengths etc.
6.2
combind fish and kelp in wide format using fish COUNT data. include area info for fish and kelp
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'. You can override using the `.groups` argument.## `summarise()` has grouped output by 'site', 'year', 'zone', 'area'. You can override using the `.groups` argument.## [1] 82 32## [1] 4023## `summarise()` has grouped output by 'site', 'year', 'area', 'zone'. You can override using the `.groups` argument.## [1] 100 18## Joining, by = c("site", "year", "zone", "area")## [1] 82 467 Quick view of what species to include in kelp ordinations. Basically only the big three have any abundance.
7.1 Algae
## `summarise()` has grouped output by 'species'. You can override using the `.groups` argument.
7.2 Fish
Note, the y-axes are very different
## `summarise()` has grouped output by 'taxa'. You can override using the `.groups` argument.
7.2.1 NOTES
for multivariate analysis; cut and paste to that file
fish.spp = c(“OPEL”, “HEXA”, “SECA”, “SCMA” ,“SENE”, “SEME”, ‘EMBI’,‘GOBI’)
yoy.spp = c(“SECAyoy”, “SEPIyoy”, “SEMYyoy”, “SEBYTyoy”,“RYOY”)
8 SOME USEFUL TABLES
9 A tibble: 6 x 4
Species Common name Group Total
## # A tibble: 6 x 4
## Species Taxa Total Density
## <chr> <chr> <dbl> <dbl>
## 1 Balanus nubilis barnacle 15892. 0.829
## 2 Strongylocentrotus purpuratus purple urchin 13657. 0.714
## 3 Nucella lamellosa shelled gastropod 5281. 0.293
## 4 Mesocentrotus franciscanus red urchin 3057. 0.160
## 5 Cucumaria miniata cucumber 1981 0.107
## 6 Styela montereyensis tunicate 1738 0.094810 Kelp Canopy
Imports data file from other R file. Plot just kelp canopy. Add to ggarrange below.
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Mean ha for 2004-2013: 700.6700019 ha +/- 43.6630069 s.e.
Total canopy 2014: 337.2999981 ha
Drop from previous decade: 0.4813964 % of previous cover.
Mean ha for 2015-2020:659.7333332 ha +/- 33.9434596 s.e.
Compared to earlier decade: 0.941575 % of previous cover.
Totals 2014 for Total, Nereo, Macro = 337.2999981, 89.6000009, 247.8999973 ha Totals 2020 for Total, Nereo, Macro = 701.8, 383.4, 318.6 ha
Change was 2.0806404, 4.2790178, 1.2851957 fold.
11 Combined Figures for MS
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12 Combined Kelp and Temperature figure
## [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10"## Note: Using an external vector in selections is ambiguous.
## i Use `all_of(sites2)` instead of `sites2` to silence this message.
## i See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
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